Update app.py

app.py

@@ -123,7 +123,7 @@ def submit_message(prompt, prompt_template, temperature, max_tokens, context_len
     embeddings = OpenAIEmbeddings()
         
     
-    history = state['messages']
+    history = state['question']
 
     if not prompt:
         return gr.update(value=''), [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)], f"Total tokens used: {state['total_tokens']}", state
@@ -160,8 +160,8 @@ def submit_message(prompt, prompt_template, temperature, max_tokens, context_len
         #    new_docsearch = pickle.load(f)
         
         docsearch = FAISS.from_texts(texts, embeddings)
-        query = str(system_prompt + history[-context_length*2:] +  [prompt_msg])
-    
+        #query = str(system_prompt + history[-context_length*2:] +  [prompt_msg])
+        query = str(system_prompt + history[0] +  [prompt_msg])
         docs = docsearch.similarity_search(query)
         #print(docs[0].page_content)
 
@@ -188,9 +188,9 @@ def submit_message(prompt, prompt_template, temperature, max_tokens, context_len
         history.append(error.copy())
 
     total_tokens_used_msg = f"Total tokens used: {state['total_tokens']}"
-    
-    chat_messages = [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)]
-    
+
+    chat_messages = [(prompt_msg['content'], completion['content'])]
+    #chat_messages = [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)]
     #chat_messages = [(history[-2]['content'], history[-1]['content'])]
     
     return '', chat_messages, total_tokens_used_msg, state